The applications and usage of the internet is expanding on a daily basis and the Internet of Things (IoT) is fast becoming the new approach for incorporating the internet into our personal, professional and social lives. IoT enables a wide variety of devices to inter-operate through the existing internet infrastructure. Capillary networks are proposed as a fundamental part of loT development, and will enable local sensor and devices to connect efficiently with other ubiquitous communication networks such as cellular systems. In this paper, we apply the Q-learning algorithm for the scheduling of capillary gateways for (M2M) communication in IoT networks. Q-learning algorithm is used to select conflict- free slot assignment for these gateways in a self-organizing manner. We analyze the performance of the proposed algorithm with respect to learning rates and rewards.
Distributed Slot Allocation in Capillary Gateways for Internet of Things Networks
01.09.2016
227437 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Wireless internet gateways (WINGs)
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